In this episode, host Gwyneth Shaw talks with Chancellor’s Clinical Professor Laurel E. Fletcher, the founding director of the Global Rights Innovation Lab Clinic (GRIL), and Valentina Rozo Angel, the clinic’s Data and Technology Clinical Supervisor.
GRIL, which enrolled its first cohort of students last year, operates at the crossroads of human rights and digital technology, developing and using data-driven tools to bolster local advocacy, policy, and social change — at home and abroad — in support of human rights defenders and victims. The clinic grew out of Fletcher’s work over more than two decades of leadership at Berkeley Law’s Human Rights Clinic. GRIL’s model allows students to build legal cases using data science analyses on large datasets and create digital storytelling tools to support policy advocacy.
To learn more, consult the clinic’s website (updated regularly) and the blueprint for GRIL, Designing Justice: Data Science for Human Rights Advocacy
About:
“Berkeley Law Voices Carry” is a podcast hosted by Gwyneth Shaw about how the school’s faculty, students, and staff are making an impact — in California, across the country, and around the world — through pathbreaking scholarship, hands-on legal training, and advocacy.
Episode Transcript
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[GWYNETH SHAW]
Hi, listeners. I’m Gwyneth Shaw, and this is Berkeley Law Voices Carry, a podcast about how our faculty, students, and staff are making an impact through path-breaking scholarship, hands-on legal training, and advocacy. I’m joined for this episode by two fantastic guests from one of the law school’s newest clinics.
Laurel Fletcher is the Chancellor’s Clinical Professor and the Founding Director of the Global Rights Innovation Lab Clinic, or GRIL. Valentina Rozo Angel is GRIL’s Data and Technology Clinical Supervisor. GRIL, which enrolled its first cohort of students in spring 2025, operates at the crossroads of human rights and digital technology, developing and using data-driven tools to bolster local advocacy, policy, and social change at home and abroad in support of human rights defenders and victims.
The clinic grew out of Fletcher’s work over more than two decades of leadership at Berkeley Law’s Human Rights Clinic. GRIL’s model allows students to build legal cases using data science analyses on large data sets, and to create digital storytelling tools to support policy advocacy. Fletcher, who is also co-faculty director of the Law School’s Miller Institute for Global Challenges and the Law, joined Berkeley Law in 1998.
Her work, including an empirical study on the impact of detention on former detainees who were held in US custody in Afghanistan and Guantanamo Bay, Cuba, has been published in law reviews and academic journals around the globe. Rozo Angel, who earned master’s degrees in economics and data science, joined GRIL in 2025 after stints at the Human Rights Data Analysis Group and as a Fox International Fellow at Yale University, where she applied supervised machine learning techniques to statistically impute responsibility for killings during the Colombian armed conflict. She was the analytics lead at Colombia’s Truth Commission, where she oversaw a team of nearly 30 researchers working with the largest human rights data set in history.
Thanks to you both for joining me.
[LAUREL FLETCHER]
Thank you.
[VALENTINA ROZO ANGEL]
Thank you.
[GWYNETH SHAW]
Laurel, the idea for GRIL emerged from your work at what was then known as the International Human Rights Law Clinic. Can you talk about the arc that led to this clinic’s founding?
[LAUREL FLETCHER]
Thanks, Gwyneth. My work at the International Human Rights Law Clinic focused on mass and systematic human rights violations. We’re looking at violations that were perpetrated by state actors, so government forces in times of peace, so under authoritarian or repressive regimes, as well as during armed conflict, violations that the state committed, violations that armed non-state actors committed, so in civil wars.
And we also looked at systemic violations that occurred against marginalized and vulnerable populations. So whether those were immigrants in the United States, whether those were restaurant workers, right? So you can have lots of types of vulnerability at the population level, which make people vulnerable to human rights violations.
So all of that work was really at the intersection of how do we prove that these violations occurred on a broad scale. The traditional techniques of human rights advocacy use individual stories, individual cases that get situated within a context or a pattern. We also try and get evidence where we can of the scope and the scale of violations, and we’ll do that through various forms of documentation.
All of this relies on stories of individuals to really illustrate in depth what the dimensions of violations mean at the individual level. But we always needed to have evidence of the scale and the scope of the problem to make the case that these were systemic or mass violations. So proving patterns and trends is just critical to the human rights work that I did.
These same problems are occurring whether you’re doing international work or you’re doing domestic work, whether you’re looking at strategic litigation on impact cases, whether you’re doing policy work, you need evidence to support your legal claims. GRIL grew out of my realization that my tools and techniques for working with evidence to show mass and systematic violations was not keeping up with the technology that was available and the tools that were available to prove those kinds of claims. Traditionally, human rights work, we’re interviewing victims, and when we want to show that violations are at scale, we interview more victims, and we look to other kinds of evidence to show that this was happening on a widespread basis.
But traditionally, human rights work, you might think of it more as investigative reporting in the terms of our orientation to the problem. And yet, the information and the information environment has changed drastically over the last 20, 25 years. We now have information, we have data, right?
Just a fancy word for information at our fingertips in multiple forms that were not available before. So we think about social media and people posting videos or posting online, witnessing events unfold in real time. That’s a form of evidence.
We also have data sets that are about climate change and temperature change. We have data sets about immigration and immigration crackdown, immigration decisions. We have data sets about armed conflict, about where we see bombs that are falling and civilian casualties, right?
There’s lots of different kinds of ways that data is now being collective and is being collected at a broad scale.
So the question is, how can human rights and social justice lawyers and advocates use that data to meet the moment, to prove claims, to push the law, to protect people against violations, against abuses of power? How can we be doing that better? So that was my impetus in starting the Global Rights Innovation Lab Clinic.
I wanted to see how we could be employing digital technologies, new forms of data analysis, and harness that with legal advocacy. So for that, I needed a data analyst because that is not my expertise. I could see the need, but I didn’t have the tools or techniques.
And so I feel incredibly lucky that I was able to bring on Valentina Rozo Ángel to work with me and build the clinic.
[GWYNETH SHAW]
Valentina, what drew you to GRIL given your background?
[VALENTINA ROZO ÁNGEL]
So let me start with answering what brought me to GRIL. I have spent my career applying quantitative-based methods to human rights advocacy, and I have always worked side by side with lawyers. And when I read the description of GRIL, it was my dream came true.
I have always wanted to be in a space in which data people and lawyers could be equally important to make a change, and I believe that is one of GRIL’s core values. And I was also very attracted by the educational aspect of it. I had worked with lawyers all my career, and I could see how important it was for them to have this data literacy, to be able to understand what statistics were, what a model is, what is artificial intelligence, and so forth and so on.
So being able to be part of a university and work together with students who are going to be the future lawyers and provide that knowledge was very interesting to me, but also being able to provide this framework to the data students. I know that there are many people who want to do data for good, and it’s not very easy to understand what that exactly means. But I do think that the human rights framework is a great framework to understand how you can make a contribution and a change.
But also the clinics, I knew that being part of Berkeley Law would allow us to work on the most important human rights-related issues all over the world, so I saw that as a perfect opportunity.
[GWYNETH SHAW]
What’s it been like to build something like this from scratch? You’re bringing in elements of some things other people have done, but really my understanding is this is pretty unique. How fun has that been, and where has it been challenging?
[LAUREL FLETCHER]
That’s a great question. One of the great joys of starting something new after a 20-year career in the field is that I had a sense that I, of a new direction where I sensed there was a need and an opportunity to do something and bring a new perspective and new tools to the human rights and social justice advocacy. I also knew that there was a great deal that I didn’t know.
So what we did, I think this was one of the best decisions that we made, is we brought in a design thinking consultant to work alongside us. Design thinking applies to social institutions like a clinic as well as a physical product, like a new toaster. The similarity is that you take the premise that what you’re building should be useful and center the user.
Who are the beneficiaries of whatever product it is that you’re trying to create? So another way to think about design thinking is human-centered design. In our case, we wanted to center GRIL, our contribution, around a use purpose.
How can we bring the application of digital technologies to human rights advocacy? We worked with a design thinking consultant and a group of students to think that through. we talked to a lot of people about what the need was.
And when we were thinking about who our stakeholders were, we thought about our potential clients. Who are the human rights organizations, social justice organizations that are out there in the world, and what are they seeing as the cutting-edge applications of technology to their work that they don’t necessarily have the tools to implement, but they see the value? We also had stakeholders as students.
Where are law students who are interested in doing public interest, private practice, really a legal practice for the digital age? And they need to know how to work with data, how to work with technology to build legal cases. And where are the technologists, the graduate students from computer science, from the Information School, from the School of Public Policy, for other data-adjacent fields, where are they?
Where are the data for good graduate students? What is it that they’re looking to get out of an experience where they can exercise their technical skills to do data for good? We’re doing a lot and trying to bring that together.
That’s what we really did last spring. We sat together over hours and hours. We did a bunch of research.
We did a bunch of interviews with stakeholders, and we pulled together a blueprint. We decided that we were going to start working in two to three areas with an idea of the kind of use cases that we could apply our skills towards. One of those is how do we work with data sets for litigation, for legal cases?
For example, how do you prove a crime against humanity with the assistance of data science? So a definition of a crime against humanity is it has to be widespread or systematic violations of a particular kind, a particular severity. So if you have evidence of those violations, can you analyze that to show that they’re widespread and systematic?
That is the integration of legal norms and data-based evidence to pull those together. We’re also looking at ways that we can do digital storytelling so that you have a particular human rights issue that you want then to illustrate. You want to make it interactive with user engagement so they can see the individual voice and case in the context of this particular experience is exemplary of a wider pattern.
How can you represent that visually? How can you tell that in a narrative way? To engage a broader public or a targeted public?
Those are both, right? So you might have decision makers who are, let’s say, working on a new international treaty. Those might be a target.
And you also might have a target audience of the general public that you want to socialize them, bring awareness to a particular kind of human rights violation. So we’re looking in different ways that we are able to apply these tools and techniques of data analysis to legal cases. And that has been really fun, and it’s also been really challenging to bring on law students and who I’ll broadly call our technology students, and to have them work together in teams on a common problem with their differentiated skill set.
[VALENTINA ROZO ÁNGEL]
I completely agree with Laurel, and I would add to that, of course, there are going to be obstacles anytime that you start something new, but I am convinced that we have had the right ingredients to overcome those obstacles. And first of all, I must start by recognizing Laurel. I know that Laurel has been very important in being a great mentor on how to succeed in the clinical setting, even if it’s a new clinic.
But we’re also part of this clinical infrastructure that has provided us everything that we need. For example, we are the first people at the law school to get a server. So we have been working together with IT to have the technical infrastructure that we need to be able to succeed at our work.
And of course, the students, initially we didn’t know if this was going to resonate with students or not necessarily, and as we were conducting the interviews for our blueprint, we understood that this was something that they wanted. They didn’t want to become the law students who coded and who were behind the computer with the numbers, but they wanted to be able to talk about these figures, understand them, and also challenge them in the future. And I also think that it has been very amazing to see how the clients have understood our value.
We didn’t have to sell them on the idea of what we provide as a difference. It has been very clear to them how they need this mix of data and legal intersection. It has been amazing to see that there is a need in the human rights sector, and we are able to provide a solution.
[LAUREL FLETCHER]
I want to talk a little bit about what we’re hearing from law students because this isn’t a vanity project of Laurel Fletcher. That would not survive. It’s not something that I’m interested in.
I’m interested in leveraging my experience to create something that’s going to be useful to human rights and social justice advocates. So for that, I hope that what we’re doing is educating a new generation of lawyers to be comfortable and knowledgeable and literate in technology. Not to make them technologists, but so that they understand that part of what being a lawyer today, if you’re going to prove a case, your evidence is likely to also be available, if not prevalent, in a digital format.
And so, how are you going to analyze that? You don’t need to be a data scientist, but you need to understand what a large language model is, and you need to have some kind of literacy about what it does do and what it doesn’t do, so that as the lawyer, you can talk to the technologists and understand what kind of computations and data analysis can be done, what the strengths of it are, what the weaknesses are, and what choices you have available to you. You still need to, as a lawyer, be steeped in the law and the norms, but you also need to be able to apply those into a digital technology information landscape.
And that’s what we’re seeing our law students do. And I saw over our first semester, which was the fall semester, we had our first time that we had clients, that students were working on live cases and projects where the law students were doing regular normative legal research. What are the rules?
And then how do those apply in this context? And they were working with facts. The facts they were working with were facts that were patterns of data.
And they understood the law so much more clearly and in greater nuance because they were constantly translating and working back and forth between what are the standards and how do we prove these standards? And working alongside technologists to understand what the data are showing and where are the gaps in the data, and how do you account for that? That type of rigorous analytic thinking is what makes good lawyers.
The facility to do that and be comfortable with data is going to make these students leaders in the current age of lawyering in a digital environment.
[VALENTINA ROZO ÁNGEL]
And I think that this is also true for the data students. Our students are people who are interested in doing this data for good or social justice, but social justice also needs a mechanism. Law is usually a very effective one.
So by them understanding this legal terminology and us understanding what data we have and how it can fall or not fall into the standards, it makes you think in a different way of the Excel spreadsheets that you get, and it opens this discussion. So to me, if you’re a law student or a data student, you’re getting a lot of value just on your field. But the main value that we’re adding is this collaboration between the two of them and learning how to understand each other’s language in a better way.
Also, asking questions to the other team. So many times when we have a great breakthrough, it’s because someone from the other team asked a great question that the legal team or the data team wasn’t asking. So you also have a different mindset and a different way of thinking about problems, and that opens a lot of opportunities for the cases and the clients.
[LAUREL FLETCHER]
So, for example, we were working on a project that was examining patterns of aerial bombardment in a conflict to see whether those were violations of the laws of war. To do that, there’s a legal standard, right? It’s war is lawful.
We can argue about whether it should be lawful, but it is lawful, and you need to follow particular rules in the conduct of war. Specifically targeting civilians, or, in this case, civilian objects, can be a violation of the laws of war, but it has to meet particular requirements. So the exercise, the legal exercise we were doing, was examining the patterns of bombardment to see if we could draw inferences that there was targeting of civilian objects that had a special legal protection.
And so for that, there was a lot of creative thinking. First, you have to clean the data. There was thousands of potential pieces of data, so we had to figure out which ones were relevant.
The data had to be sorted and analyzed so that we could begin to see what kinds of objects were in the data set and determine through other ways whether those objects met the standards of being eligible for special protection, and then whether the patterns of bombardment suggested that they were specific targeting. So you can imagine there’s a lot of case law that discusses how can you determine whether there was intent based on the aftermath, right? What are the facts of the damage and how do you infer intent?
So there was a lot of legal research on that. And then there was looking at the dataset itself and thinking creatively about what are some of the other indicia can we identify that might tell us something about whether the targeting was intentional. So for example, can we learn anything about the time of day that bombs were dropped on particular protected objects like schools?
So if we could learn that schools were being bombed during the school day, that might be a really important piece of information. That’s a small example of that type of exchange that I can distill into a couple of sentences, which took hours and hours of work to be able to identify what were the possibilities that were before us, that we could then make an evaluation about what the legal weight of the evidence that we had identified could be.
[GWYNETH SHAW]
How difficult is it to find these sources of information? I’m sure it depends on what you’re looking for, but is that something that takes a lot of time as well before you even get to the stage where you begin to clean it up and analyze it?
[VALENTINA ROZO ÁNGEL]
I don’t think it’s very difficult because most of the human rights organizations are very good at documenting the human rights violations. So in general, we work with clients who have gathered their own data. And the question that they have for us is, how do we analyze it?
We receive the data directly from them, but I must say that something that we have learned is that another contribution that we can make is not only about the analysis, but also the documentation itself. We work with organizations that do not necessarily have lawyers. So when they are trying to solve a legal question, maybe the way in which they have been collecting the data is not a perfect fit with what the legal standard requires.
So another contribution that we’re making is in this collaboration between the data teams and the legal teams, providing feedback on how to modify their documentation efforts to make sure that they fall under the legal categories that are needed to bring a potential case.
[GWYNETH SHAW]
Laura, you mentioned earlier about the students, them being involved in figuring out how to make this into a clinic. What are you hearing from students now that you’ve had a cohort come through, and what’s their experience like, and how do they feel like this is enhancing their legal education?
[LAUREL FLETCHER]
So what’s interesting about the question, and what’s interesting about what students have told us is that, I mean, we’re at Berkeley Law, students are interested in doing lots of different kinds of legal practice. So we have students who are in the clinic who are going to go on and do transactional business law practice, and they’re saying, “I can see how what I’m learning in GRIL is going to be applicable to my future practice, because when we’re talking about patterns in financial markets, I know I’m going to be able to talk to the experts there and understand better the kind of evidence that we need on the legal side to understand what’s going on in the markets. We have students who want to go into an environmental law practice or who want to go into a technology law practice, and they are saying, “Oh, now I understand these concepts.
Now I see how they apply.” We have students who are looking to go into an international law practice. And they’re saying, “I now understand both the international law better, but I also understand how to make international law arguments and how to marshal evidence for those arguments.
I feel gratified to hear from law students who are in the clinic and who are going to pursue a wide variety of careers, that they’re learning valuable skills while they are also working on cases and projects that align with their values. So I think that’s– law school should give them the opportunity to develop the skills, and also the opportunity to develop an experience of doing a legal practice that aligns with their values, and we’re able to offer our students both.
[GWYNETH SHAW]
Where do you see GRIL as a clinic and this corner of the clinical realm, and even maybe the legal realm, in five or ten years? There has been a lot of growth in empirical studies in law in the past 15 or 20 years. Where do you think this is going to go, and where would you like to see it go, both at Berkeley Law and in general?
[LAUREL FLETCHER]
I really think that this clinic could only have started at Berkeley Law. I don’t think that I would have had the confidence or the support anywhere else to start a clinic that breaks the mold. There is no clinic like this out there, and the dean, Erwin Chemerinsky, when I told him of my idea, he said, “This sounds really interesting.”
If this is what you want to explore, then I’m going to back you one hundred percent.” I reached out to colleagues. We have the best law and technology faculty in the country, and I reached out to them and said, “Hey, this is what I’m thinking of doing.
What do you think?” Overwhelming support. “That sounds super interesting.
I can see how it’s complementary to what we have, but it’s different. How can we help?” The same with my clinical colleagues.
They were also like, “This sounds really interesting. How does it complement what we’re doing? How can we help?”
And the students, right, we have a cohort of students in the law school who come to Berkeley Law because they’re interested in technology. That gave me the confidence to say, “Okay, I think there’s going to be interest here in the student body,” right? We have a strong social justice student body.
We have a strong student body that’s interested in technology, and there’s overlap among those communities. And we have just a curious student body who are willing to take a risk and say, “This sounds like something that is valuable and is going to be interesting, so I want to take a chance.” That was great.
What I didn’t know, and which Valentina has been instrumental, is where were the data-for-good students across the campus? Valentina, we’ll let her talk about how she has reached out and what that response has looked like. But it’s really been this complement of talents and energies that have come together to make this type of clinic possible.
My intuition is that the law practice is changing, and having students gain comfort and literacy with how to use data is going to become only more and more important. Why do I think that? We’re hearing it from our clients.
They see the need, but they didn’t have the human infrastructure to apply those kinds of techniques within their organization. That’s why they’re looking to us. I think in five, 10 years, when we have graduated students who have those capacities, you’re just gonna see more and more of that out there.
So I think there’s going to be a demand for the skills and the aptitude that our students are developing within GRIL, out in the legal academy. And I would love to see more clinics like this, whether they start in human rights or they start in criminal law or environmental law, anywhere where you’re looking at violations that are occurring on a widespread basis, right? So you can look across immigration, criminal justice, environment, poverty law.
You’re looking at problems where there is data about the problem that’s happening at scale, and you need to marry that data to make policy change, to bring litigation, to make legal claims. So I would love to see this component of data analytics and law get incorporated throughout more clinics at Berkeley and obviously across the United States.
[VALENTINA ROZO ÁNGEL]
Regarding the response from data students, it has been incredible. So initially, you can imagine that we were not cross-listed with any other school. So if students wanted to join the clinic, they had to follow a specific process, and they made it.
So we initially reached out to students from Goldman and from the iSchool, and we found that there is a real interest in social justice, but the question was, “How can I actually do this?” And they found that GRIL was a great opportunity for them. We also continued talking to other faculty at the university, so we started talking to professors from statistics, from engineering, also from design, for example, and we have seen that the response is, as Rula was saying, very positive.
This sounds very interesting, very important, very relevant. How can we help? So building GRIL hasn’t been something that we have done together.
It has been by being part of this ecosystem that we have been able to find the right people to help us connect with other people who want to make a change. And I think that in five to 10 years, the multidisciplinary work that we are doing today will be the standard practice. I think that GRIL is a pioneer or an early adopter that is creating this blueprint for others to follow.
But it will become very clear that for a lawyer to be successful and effective in their career, they need to be fluent in technical concepts and know how to collaborate with data scientists, especially now that we have AI and you have to use technology, and probably many of the evidence that you will start using or the data that you will gather will be from this new era of massive documents, pictures, videos, et cetera. You need to understand what the models can and what they cannot do. So I feel that in five to 10 years we will see many clinics doing this type of work in collaboration with different fields.
[GWYNETH SHAW]
Thank you both for this great conversation. I think this is incredibly interesting, and I look forward to seeing where you’re going to take all this great work.
[LAUREL FLETCHER]
Thank you, Gwyneth.
[VALENTINA ROZO ÁNGEL]
Thank you.
[GWYNETH SHAW]
And thank you, listeners. To learn more about Professor Fletcher, her work, and GRIL, please check out the show notes. If you enjoyed this episode, please share it, and be sure to subscribe to Voices Carry wherever you get your podcasts. Until next time, I’m Gwyneth Shaw.
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